In wireless communications systems the power amplifier (PA) employed in base stations is a potential source of distortion. Such distortion is undesirable, especially where it causes InterModulation Distortion (IMD) components out of the spectral band allocated for the carrier since such out of band distortion is tightly regulated by the FCC (and similar bodies in other countries). One approach to reducing such distortion is to operate the amplifier in a backed off region below its maximum power capability where the amplifier is more linear. This requires a larger amplifier than would otherwise be the case, however, making the system less efficient and more expensive. This problem is made more severe by modern wide bandwidth modulation schemes, such as CDMA, WCDMA and UMTS, which employ signals with large random signal peaks. Therefore, it is highly desirable to reduce distortion while maintaining amplifier efficiency by reducing distortion without simply making the amplifier bigger. One approach to this goal is amplifier linearization using predistortion to correct for amplifier nonlinearities.
Linearization of RF power amplifiers using predistortion is a well-studied field. There are various parameters that can be used to classify predistortion approaches. One very important parameter is the form of the transmitted signal at the point where the predistortion is applied. The transmitted signal at the point where the predistortion is applied may be a digital signal, an analog intermediate frequency (IF) signal, or an analog radio frequency (RF) signal. In most approaches, it is the same form as the input signal to the system.
In digital predistortion, digital signal processing is used to generate the compensation for PA nonlinearities and the distortion they generate. When the available input signal is in a digital format, digital predistortion is a natural choice. The benefit of digital predistortion is that accurate compensation models can be created allowing for the largest amount of linearization of any of the predistortion classes. In addition, the digital predistortion approaches match well with adaptive systems whose coefficient estimation is performed digitally. The primary disadvantage of digital predistortion is that the available input signal is often RF, and it would cause excessive delay and cost to down-convert and digitize the available signal. Therefore, there is a broad class of amplifier applications where analog predistortion is the only practical approach.
Analog predistortion approaches may in turn use digital processing by deriving a baseband signal from the input analog signal envelope, performing an analog to digital conversion, performing the digital baseband processing to derive digital predistortion signals, converting the digital predistortion signals to analog form, then applying the analog predistortion signals to the input signal to predistort the signal. This approach suffers from undesirable time delays in the parallel predistortion path to allow time for the digital baseband processing. This requires large delay lines in the main signal path introducing undesirable power losses and system size, weight and cost. Analog predistortion approaches may alternatively use analog processing to derive predistortion signals. Such approaches, however, have suffered from a lack of ability to sufficiently accurately model the predistortion needed to correct the amplifier nonlinearities. This is particularly the case for large modulation bandwidths and high peak to average signals of the type noted above which are commonly employed in many modern communications systems.
Accordingly a need presently exists for a predistortion approach which can address the above noted problems and provide effective amplifier linearization employing analog predistortion where digital predistortion is not practical.